On the runtime analysis of the 1-ANT ACO algorithm

The runtime analysis of randomized search heuristics is a growing field where, in the last two decades, many rigorous results have been obtained. These results, however, apply particularly to classical search heuristics such as Evolutionary Algorithms (EAs) and Simulated Annealing. First runtime analyses of modern search heuristics have been conducted only recently w. r. t. a simple Ant Colony Optimization (ACO) algorithm called 1-ANT. In particular, the influence of the evaporation factor in the pheromone update mechanism and the robustness of this parameter w. r. t. the runtime behavior have been determined for the example function OneMax. This paper puts forward the rigorous runtime analysis of the 1-ANT on example functions, namely on the functions LeadingOnes and BinVal. With respect to EAs, such analyses have been essential to develop methods for the analysis on more complicated problems. The proof techniques required for the 1-ANT, unfortunately, differ significantly from th...

• Type: Conference
• Year: 2007
• Where: GECCO
• Authors: Benjamin Doerr, Frank Neumann, Dirk Sudholt, Carsten Witt
• Keywords: GECCO 2007, Randomized Search Heuristics, Runtime Analysis, Search Heuristics